---
license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-tapera
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# sentiment-tapera

This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6966
- Accuracy: 0.8455
- Precision: 0.7812
- Recall: 0.7567
- F1: 0.7675

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6236        | 1.0   | 90   | 0.5920          | 0.8049   | 0.5358    | 0.5904 | 0.5575 |
| 0.363         | 2.0   | 180  | 0.4065          | 0.8374   | 0.7515    | 0.7181 | 0.7322 |
| 0.1506        | 3.0   | 270  | 0.4414          | 0.8537   | 0.8191    | 0.7303 | 0.7606 |
| 0.0619        | 4.0   | 360  | 0.6592          | 0.8496   | 0.8036    | 0.7151 | 0.7420 |
| 0.0261        | 5.0   | 450  | 0.6966          | 0.8455   | 0.7812    | 0.7567 | 0.7675 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1